sequor

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Sequor is a sequence labeler based on Collins's (2002)perceptron. Sequor has a flexible feature template language and ismeant mainly for NLP applications such as Named Entity labeling, Partof Speech tagging or syntactic chunking. It includes the SemiNER namedentity recognizer, with pre-trained models for German and English (see`Named Entity Recognition (SemiNER)`_).

Sequor is especially useful if your dataset has a large label set. Inthis case it is likely to run faster and allow you to use much lessRAM than a sequence labeler based on Conditional RandomFields. Additionally sequor implements options which allow you tocontrol the size of model and tradeoff speed against accuracy:

Cabal should then download and install the necessary packages, andinstall the sequor binary in ./bin, and the data files in ./share

Usage-----With Sequor you can learn a model from sequences manually annotatedwith labels, and then apply this model to new data in order to addlabels. Sequor is meant to be used mainly with linguistic data, forexample to learn Part of Speech tagging, syntactic chunking or NamedEntity labeling::